STIR Atlas Summer Work

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STIR Atlas Summer Work

  1. 1. Brain Atlas <ul><li>Dan Diner </li></ul>
  2. 2. Introduction <ul><li>PET is a nuclear </li></ul><ul><li>imaging technique </li></ul><ul><li>Tracer concentrations in brain are recorded </li></ul><ul><li>The information collected is used for brain study, disorder analysis, and diagnosis </li></ul>
  3. 3. ROI/VOI Mapping <ul><li>ROIs(Regions of Interest) are small regions mapped onto brains </li></ul><ul><li>Ussualy mapped out manually- very time-consuming and requires highly-paid personnel (raters) </li></ul><ul><li>Raters have inter- and intra- subject variation </li></ul><ul><li>As PET scan quality increases, so does the time it takes for raters to do their job </li></ul>
  4. 4. <ul><li>PET has poor spatial resolution, high temporal </li></ul><ul><li>MRI has high spatial resolution </li></ul><ul><li>ROIs are therefore mapped onto the MRI of a subject, onto which the PET scan is co-registered </li></ul>
  5. 5. MRI PET Co-Registered
  6. 6. Brain Atlases <ul><li>An “average brain” with previously labeled VOIs (Volumes of Interest) </li></ul><ul><li>labels those VOIs onto inputted images </li></ul><ul><li>Never have been as accurate as manual methods, but very precise - no inter- or intra- subject variation </li></ul><ul><li>much faster than manual methods </li></ul>
  7. 7. Brain Atlases <ul><li>Many labs make their own. </li></ul><ul><li>Each different because each lab has own labelling method </li></ul><ul><li>Could be single- or multiple-sibject </li></ul><ul><li>Could be made for only one specific region or many </li></ul><ul><li>Probabilistic atlases tell you the probability of a certain voxel belonging to a certain ROI </li></ul>
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  9. 9. Methods and Materials: Subject and Image Acquisition <ul><li>MRIs and PETs from 176 subjects of past studies </li></ul><ul><li>123 from a 1.5 Tesla MRI </li></ul><ul><li>53 from a 3.0 Tesla </li></ul>
  10. 10. Image Analysis Setup <ul><li>Worked on a PowerMac G5 using Mac OS X 10.5.4 Leopard </li></ul><ul><li>Major Software used: </li></ul><ul><li>Matlab (R2007a) </li></ul><ul><li>FSLVIEW and FLIRT </li></ul><ul><li>ART </li></ul><ul><li>iView </li></ul>
  11. 11. Image Pre-Processing <ul><li>Raw MRI files were </li></ul><ul><li>copied to a common </li></ul><ul><li>folder </li></ul>
  12. 12. <ul><li>Raw MRI images multiplied(matrix multiplication) by GM, WM, and CSF masks </li></ul><ul><li>This got rid of all extraneous material (neck, skull, dura matter) </li></ul><ul><li>Extraneous material messes with result data </li></ul>
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  15. 15. <ul><li>Used iView to compare new images against raw ones </li></ul><ul><li>This was done to look for undeleted extraneous material and accidentally segmented brain </li></ul><ul><li>I used a scale of 0-3 to rate the new images (0= perfect, 1=some dura, 2=much dura, 3=segmented brain) </li></ul><ul><li>Most images were 0s and 1s. </li></ul>
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  17. 17. Normalization Procedure <ul><li>Normalization is moving an image into a standard space </li></ul><ul><li>MNI template to which were were normalizing was reoriented towards raw MRI native space </li></ul><ul><li>New MRI images also normalized to this template </li></ul><ul><li>We examined the normalized images, and found that some were very well aligned, but others were misplaced or improperly warped </li></ul>
  18. 18. <ul><li>warping is normalization Degrees of Freedom 9-12 </li></ul><ul><li>ART uses a 2-step process to warp MRIs: linear registration, then warp </li></ul><ul><li>Because the rotation was bad, we thought that the linear registration had gone wrong </li></ul><ul><li>We tried linear registration with FLIRT, and then warping with ART </li></ul>
  19. 19. <ul><li>The rotations came out looking good, but close inspection revealed that some leftover dura got warped into the new brain </li></ul>
  20. 20. <ul><li>An MRI with a particularly large amount of dura was manually cleaned, and then had FLIRT and ART run on it </li></ul><ul><li>The resulting image was perfect </li></ul>
  21. 21. Conclusion <ul><li>ART is very sensitive to extraneous material </li></ul><ul><li>all dura needs to be properly removed from all images before normalization </li></ul><ul><li>A better automatic method for cleaning up dura needs to be developed </li></ul>

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